iSEA Knowledge Hub
Bio Image Analysis Tools
Featured Article
A Hitchhiker's guide through the bio-image analysis software universe
FEBS Lett. 2022 Oct;596(19):2472-2485.
Bioimage data are generated in diverse research fields throughout the life and biomedical sciences. Its potential for advancing scientific progress via modern, data-driven discovery approaches reaches beyond disciplinary borders. To fully exploit this potential, it is necessary to make bioimaging data, in general, multidimensional microscopy images and image series, FAIR, that is, findable, accessible, interoperable and reusable. These FAIR principles for research data management are now widely accepted in the scientific community and have been adopted by funding agencies, policymakers and publishers. To remain competitive and at the forefront of research, implementing the FAIR principles into daily routines is an essential but challenging task for researchers and research infrastructures. Imaging core facilities, well-established providers of access to imaging equipment and expertise, are in an excellent position to lead this transformation in bioimaging research data management.
Image processing tools for petabyte-scale light sheet microscopy data
Light sheet microscopy is a powerful technique for high-speed three-dimensional imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations. To address these challenges, we present PetaKit5D, a scalable software solution for efficient petabyte-scale light sheet image processing. This software incorporates a suite of commonly used processing tools that are optimized for memory and performance. Notable advancements include rapid image readers and writers, fast and memory-efficient geometric transformations, high-performance Richardson–Lucy deconvolution and scalable Zarr-based stitching. These features outperform state-of-the-art methods by over one order of magnitude, enabling the processing of petabyte-scale image data at the full teravoxel rates of modern imaging cameras. The software opens new avenues for biological discoveries through large-scale imaging experiments.
PetaKit5D
Tools for efficient and scalable processing of petabyte-scale 5D live images or large specimen images from lattice light-sheet microscopy (LLSM) and other light sheet microscopies, as well as other imaging modalities. It is featured by fast image readers and writers (for Tiff and Zarr), combined image deskew/rotation, instantly converged Richardson-Lucy (RL) deconvolution, and scalable Zarr-based stitching.
Napari
Napari is a Python library designed for n-dimensional image visualization, annotation, and analysis. It enables users to explore 2D, 3D, and higher-dimensional arrays on a canvas, overlay data such as points, polygons, and segmentations, and annotate or edit datasets using standard structures like NumPy or Zarr arrays.
Amira (for Life Sciences)
Thermo Scientific Amira Software is a powerful, comprehensive, and versatile software solution for visualizing, analyzing and understanding life science and biomedical research images from many image modalities, including Optical and Electron Microscopy, CT, MRI and other imaging modalities.
Bio Image Data Management Platform
Featured Article
A practical guide to bioimaging research data management in core facilities
Journal of Microscopy, 294, 350–371.
Bioimage data are generated in diverse research fields throughout the life and biomedical sciences. Its potential for advancing scientific progress via modern, data-driven discovery approaches reaches beyond disciplinary borders. To fully exploit this potential, it is necessary to make bioimaging data, in general, multidimensional microscopy images and image series, FAIR, that is, findable, accessible, interoperable and reusable. These FAIR principles for research data management are now widely accepted in the scientific community and have been adopted by funding agencies, policymakers and publishers.
I3D:bio – Information Infrastructure for BioImage Data
A Microscopy Research Data Management Resource
For researchers, the organization of raw data, and a good strategy to document the full provenance throughout a data life cycle is an important aspect of good scientific practice. Large file sizes and proprietary formats make data handling demanding. In particular, when data must be shared with other researchers in a collaborative setting, keeping track of when who did what to the data, how data was transfered, and if all steps are properly audited is a time-consuming challenge for many experimentalists.
Cytomine
This software was developed starting in 2010 at the University of Liege as a platform for histopathology image analysis. The open-source project available under https://cytomine.org is accessible publicly (not to be confused with cytomine.com, which is a for-profit corporation selling services on top of the software). Since the primary purpose for which cytomine was developed is histology, the software is mostly known for this type of data. However, the functionality of Cytomine extends well beyond the needs of histology, and can be used for bioimaging data management in general (or other images from a broad range of research disciplines – also beyond the life science domains).
A focus of Cytomine has become to enable the integration of images from multiple imaging modalities (e.g., correlated light and electron microscopy) and to incorporate them together in image analysis workflows. Cytomine can be installed as a central service at the institution or can be run by single users on their desktop PC or laptop. The Cytomine developers are creating a web platform for access to data through the internet so that image annotations and running image analysis algorithms on the images can be done from remote locations, and by many collaboration partners. Natively, the software supports many 2D file formats and pyramid resolutions that are frequently used in histology. Via the Bio-Format and other libraries, additional file formats can be loaded via pre-conversion steps.
CATMAID (Collaborative Annotation Toolkit for Massive Amounts of Image Data)
The Collaborative Annotation Toolkit for Massive Amounts of Image Data was developed by Saalfeld et al. (2009) and serves collaboratively work on large image data sets. A feature of CATMAID is that it allows to load data from other internet accessible storage locations without duplicating the data. It has been used frequently in neurobiology research projects, for example to identify large maps of neuron connectomes from large EM datasets of different animals and developmental stages.
CATMAID can be installed as a central instance or used by invidual labs.
XNAT (Extensible Neuroimaging Archive Toolkit)
XNAT originated from a Neuroinformatics Research Group at the Washington University School of Medicine (Marcus et al, 2007). Originally named eXtensible Neuroimaging Archive Toolkit, the XNAT platform has developed over the years into a versatile data management tool accepting imaging and non-imaging data. Yet, XNAT is predominantly used in the field of neuroimaging, in the preclinical and in the clinical context where imaging modalities often produce data in DICOM format (e.g., MRI, ultrasound, PET and CT data). XNAT offers options for data anonymization.
The XNAT software is a versatile tool that can be installed as stand-alone application on researchers computers or be set up as a central or multi-center instance for collaborative research. XNAT is often used in medical and pre-clinical imaging areas, but suitable for microscopy data, too.
XNAT Central and Open Access Series of Imaging Studies are examples of respositories based on XNAT to publicly share imaging data.
BisQue (Bioimage Semantic Query User Environment)
The web-platform BisQue has been developed at University of California, Santa Barbara, as a combined image organization and image analysis platform (Kvilekval et al., 2010).
It is an image data management system enabling to store and visualize bioimaging data, render and share data, analyse or connect to analysis software, enrich data with metadata.
In BisQue (Bioimage Semantic Query User Environment), images are stored in original file formats and converted to an open file format upon presentation to the user. For basic quantitative image analysis, BisQue offers modules, e.g., to make measurements in images in the web browser. Several modules exist to enable compatibility of BisQue with external analysis software.
OMERO – OME Remote Objects
OMERO (OME Remote Objects) is an open-source software product developed by the Open Microscopy environment consortium. It is an image data management system enabling to store and visualize bioimaging data, render and share data, analyse or connect to analysis software, enrich data with metadata (Key-Value pairs & Tags), and more…
According to the 2021 NFDI4BIOIMAGE community survey, OMERO was the best-known and most widely used image data management platform among core facilties and researchers in Germany (Schmidt & Hanne, 2022). Based on the open-source code, a large community of maintainers and developers around OMERO contribute to new functions, e.g., the Metadata Editor OMERO.mde (Kunis et al, 2021), or scripts to upload csv-tables as metadata annotations. OMERO can be used by researchers via a web-browser (OMERO.web). Introduction videos about OMERO can be found online (e.g., in the Global BioImaging Workshop from January 2022)
Online Educational Learning
Thermo Electron Microscopy Learning Center
Electron microscopy (EM) brings imaging and analysis to a wide variety of samples across countless disciplines and industries. With EM, scientists and researchers can see the miniature micro- and nano-scale world all around us; anything from the interior of a human cell down to the arrangement of individual atoms in a metal alloy. By studying the very building blocks of matter, we broaden our understanding of ourselves, our world, and even our universe.
This page provides a variety of informational and educational resources on electron microscopy for students, educators, or anyone that simply wants to learn more about this fascinating technology.
Andor Microscopy School
This free course introduces the basics of detectors, fluorescence microscopy, sample preparation, and confocal microscopy. It also covers advanced techniques like TIRF, super-resolution, and photostimulation, and ends with an overview of post-processing and image analysis tools.
Microlist
Microlist is a searchable database of listings for people who use light and electron microscopes. You may also want to check out the Special Interest topics, where we have tagged listings that are particularly relevant for core facilities, teachers, diversity & inclusion, and career development
MyScope
MyScope was developed by Microscopy Australia to provide an online learning environment for those who want to learn about microscopy. The platform provides insights into the fundamental science behind different microscopes, explores what can and cannot be measured by different systems and provides realistic operating experiences on the microscope simulators.
iBiology
This free online comprehensive series begins with the basics of optics, proceeds through transmitted light microscopy, covers the various methods of imaging fluorescent samples, describes how cameras work and image processing, and concludes with some of the latest advances in light microscopy.